Soil communities following clearcut and salvage harvest have different early successional dynamics compared with post-wildfire patterns
Bibliographic record
Abstract
Abstract Understanding the impacts of harvest and subsequent silviculture practices at stand scales on the below-ground biota, and their associated nutrient cycling processes, is needed to more fully evaluate the sustainable management of boreal forest systems. While stand replacing wildfire is the primary natural disturbance mechanism in jack pine-dominated boreal forest systems; clearcut harvest also results in stand renewal so is sometimes used in silvicultural systems to emulate natural disturbance and renewal processes. In this study, we simultaneously assessed the successional trajectories of three major taxa of the below ground soil community, bacteria, fungi, and arthropods using DNA metabarcoding. The objectives of this study were to use a chronosequence framework to: 1) assess whether the soil communities following clearcut harvest and wildfire converge along a successional gradient, 2) assess when the soil community recovers following clearcut harvest to the pre-disturbance, mature, wildfire reference condition, and 3) assess the effects of cumulative disturbance on soil community succession (i.e., wildfire followed by salvage harvesting of fire-killed trees). We found that richness (alpha diversity) did not illustrate any clear patterns of convergence and could, therefore, underestimate recovery times, especially for soil arthropods. Comparisons of the underlying community composition (beta diversity) proved to be more informative. In this case, we found that different soil taxa following clearcut harvest recovered on different timelines compared with succession following stand-replacing wildfire. In general, bacteria appear to be the first to converge to post-wildfire conditions followed by arthropods, however, fungi did not converge within the time frame of the chronosequence. This suggests that more extended periods are required to achieve complete recovery of the soil fungal community to the pre-disturbance condition. The cumulative disturbance associated with salvage harvest appeared to have a greater (compounded) effect on soil communities when compared with wildfire or clearcut harvest. This work showcases the performance of a scalable method for monitoring a diverse arrange of soil biota using DNA metabarcoding. In future work, tracking fungal and arthropod soil communities may provide more insights into the longer-term effects of current forest management practices and provide guidance when comparing alternative approaches. Open Research Statement Sequences have been deposited to the NCBI SRA under the GRDI-Ecobiomics project accession PRJNA565010 for the BioSample accessions SAMN26926703 - SAMN26926795 used in this study. The MetaWorks v1.9.3 multi-marker metabarcode bioinformatic pipeline is available from https://github.com/terrimporter/MetaWorks . The ITS classifier based on the ITS UNITE+INSD full dataset v8.2 and trained to work with the RDP Classifier ( https://github.com/terrimporter/UNITE_ITSClassifier ). The COI classifier v4 is available from https://github.com/terrimporter/CO1Classifier . The code used to produce figures, including infile and metadata files, will be available on https://github.com/terrimporter/Chronosequence_HarvestType .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".